Apoptotic exosome-like vesicles regulate endothelial gene expression, inflammatory signaling, and function through the NF-κB signaling pathway
Bibliographic record
Abstract
Persistent endothelial injury promotes maladaptive responses by favoring the release of factors leading to perturbation in vascular homeostasis and tissue architecture. Caspase-3 dependent death of microvascular endothelial cells leads to the release of unique apoptotic exosome-like vesicles (ApoExo). Here, we evaluate the impact of ApoExo on endothelial gene expression and function in the context of a pro-apoptotic stimulus. Endothelial cells exposed to ApoExo differentially express genes involved in cell death, inflammation, differentiation, and cell movement. Endothelial cells exposed to ApoExo showed inhibition of apoptosis, improved wound closure along with reduced angiogenic activity and reduced expression of endothelial markers consistent with the first phase of endothelial-to-mesenchymal transition (endoMT). ApoExo interaction with endothelial cells also led to NF-κB activation. NF-κB is known to participate in endothelial dysfunction in numerous diseases. Silencing NF-κB reversed the anti-apoptotic effect and the pro-migratory state and prevented angiostatic properties and CD31 downregulation in endothelial cells exposed to ApoExo. This study identifies vascular injury-derived extracellular vesicles (ApoExo) as novel drivers of NF-κB activation in endothelial cells and demonstrates the pivotal role of this signaling pathway in coordinating ApoExo-induced functional changes in endothelial cells. Hence, targeting ApoExo-mediated NF-κB activation in endothelial cells opens new avenues to prevent endothelial dysfunction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".